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164篇 您的检索式:作者名="Fergus R"
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1Refining pathological evaluation of neoadjuvant therapy for adenocarcinoma of the esophagus显示文摘AIM:To assess tumour regression grade(TRG)and lymph node downstaging to help define patients who benefit from neoadjuvant chemotherapy.METHODS:Two hundred and eighteen consecutive patients with adenocarcinoma of the esophagus or gastro-esophageal junction treated with surgery alone or neoadjuvant chemotherapy and surgery between 2005and 2011 at a single institution were reviewed.Triplet neoadjuvant chemotherapy consisting of platinum,fluoropyrimidine and anthracycline was considered for operable patients(World Health Organization performance status≤2)with clinical stage T2-4 N0-1.Response to neoadjuvant chemotherapy(NAC)was assessed using TRG,as described by Mandard et al.In addition lymph node downstaging was also assessed.Lymph node downstaging was defined by cN1 at diagnosis:assessed radiologically(computed tomography,positron emission tomography,endoscopic ultrasonography),then pathologically recorded as N0 after surgery;ypN0 if NAC given prior to surgery,or pN0if surgery alone.Patients were followed up for 5 years post surgery.Recurrence was defined radiologically,with or without pathological confirmation.An association was examined between t TRG and lymph node downstaging with disease free survival(DFS)and a comprehensive range of clinicopathological characteristics.RESULTS:Two hundred and eighteen patients underwent esophageal resection during the study interval with a mean follow up of 3 years(median follow up:2.552,95%CI:2.022-3.081).There was a 1.8%(n=4)inpatient mortality rate.One hundred and thirty-six(62.4%)patients received NAC,with 74.3%(n=101)of patients demonstrating some signs of pathological tumour regression(TRG 1-4)and 5.9%(n=8)having a complete pathological response.Forty four point one percent(n=60)had downstaging of their nodal disease(cN1 to ypN0),compared to only 15.9%(n=13)that underwent surgery alone(pre-operatively overstaged:cN1 to pN0),(P<0.0001).Response to NAC was associated with significantly increased DFS(mean DFS;TRG 1-2:5.1years,95%CI:4.6-5.6 vs TRG 3-5:2.8 years,95%CI:2.2-3.3,P<0.0001).Nodal down-staging conferred a significant DFS advantage for those patients with a poor primary tumour response to NAC(median DFS;TRG 3-5 and nodal down-staging:5.533 years,95%CI:3.558-7.531 vs TRG 3-5 and no nodal down-staging:1.114 years,95%CI:0.961-1.267,P<0.0001).CONCLUSION:Response to NAC in the primary tumour and in the lymph nodes are both independently associated with improved DFS.Fergus Noble Luke Nolan Adrian C Bateman James P Byrne Jamie J Kelly Ian S Bailey Donna M Sharland Charlotte N Rees Timothy J Iveson Tim J Underwood Andrew R Bateman 2013World Journal of Gastroenterology2013,19,48:4
2A prospective feasibility study of sub-millisievert abdominopelvic CT using iterative reconstruction in Crohn’s disease显示文摘Siobhan B O’Neill Patrick D Mc Laughlin Lee Crush Owen J O’Connor Sebastian R Mc Williams Orla Craig Anne Marie Mc Garrigle Fiona O’Neill Jackie Bye Max F. Ryan Fergus Shanahan Michael M Maher 2013European Radiology2013,,:2
3Spectral Hashing显示文摘Weiss Y Torralba A Fergus R 2008Advances in Neural Information Processing Systems2008,21,:1
4Removing camera shake from a single photograph显示文摘Fergus R Singh B Hertzrnann A 2006ACM Transactions on Graphics2006,25,3:1
5Removing Cam- era Shake from a Single Photograph 显示文摘FERGUS R SINGH B HERTZMANN A 2006ACM Transactions on Graphics2006,25,3:1
6Image and depth from a conventional camera with a coded aperture 显示文摘Levin A Fergus R Durand F 2007ACM Trans on Graphics2007,26,3:1
7Learning Generative Visual Models frbm Few Training Examples: An Incremental Bayesian Approach Tested on 101 Object Categories显示文摘Li F F Fergus R Perona P 2007Computer Vision and Image Understanding2007,106,1:1
8Image and depth from a conventional camera with a coded aperture显示文摘Levin A Fergus R Durand F 2007ACM Transactions on Graphics2007,26,3:1
9Analysis of effects of the state of charge on the formation and growth of the deposit layer on graphite electrode of pouch type lithium ion polymer batteries显示文摘Agubra V A Fergus J W Fu R J 2014Journal of Power Sources2014,270,:1
10Learning generative visual models from few training examples: an incremental Bayesian approach tested on 101 object categories显示文摘LI Feifei FERGUS R PERONS P 2007Special Issue on Generative Model Based Vision2007,106,1:1
11Weakly supervised scale-invariant learning of models for visual recognition显示文摘Fergus R Perona P Zisserman A 2007Intemational Journal of Computer Vision2007,71,3:1
12Removing camera shake from a single photograph显示文摘Fergus R Singh B Hertzmann A 2006ACM Transactions on Graphics2006,25,3:1
13Image and depth from a conventional camera with a coded aperture 显示文摘Levin A Fergus R Durand F 2007ACM Transactions on Graphics (TOG)2007,26,3:1
14Learning generative visual models from few training examples:an incremental Bayesian approach tested on 101 object categories显示文摘Li Feifei Fergus R Perona P 2007//Computer Vision and Image Understanding Special issue on Generative Model Based Vision2007,106,1:1
15Removing camera shake from a single photograph 显示文摘Fergus R Singh B Hertzmann A 2006Acm Transactions on Graphics2006,25,3:1
16Learning generative visual models from few training examples: an incremental Bayesian approach tested on 101 object categories显示文摘LI F F FERGUS R and PERONA P 2007Computer Vision and Image Understanding2007,106,1:1
17Image and depth from a conventional camera with a coded aperture显示文摘Levin A Fergus R Durand F 2007Acm Transactions on Graphics2007,26,3:1
18Weakly supervised scale-invariant learning of models for visual recognition 显示文摘Fergus R Perona P and Zisserman A 2007International Journal of Computer Vision2007,71,3:1
19lmage and depth from a conventional camera with a coded aperture显示文摘Levin A Fergus R Durand F 2007ACM Transactions on Graphics2007,26,3:1
20Learning generative visual models from few training examples:an incremental Bayesian approachtested on 101 object categories显示文摘FERGUS F F L R PERONA P 2007Computer Vision and Image Understanding2007,106,1:1
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